Apportioning black carbon to sources using highly time-resolved ambient measurements of organic molecular markers in Pittsburgh

We present highly time-resolved measurements of organic molecular markers in downtown Pittsburgh, which are used to investigate sources contributing to atmospheric aerosols in the area. Two-hour average concentrations of condensed-phase and semivolatile organic species were measured using a Thermal Desorption Aerosol GC/MS (TAG). Concentrations for mobile source markers like hopanes had regular diurnal and day-of-week patterns. Pairing high time-resolved measurements with meteorological data helped identify contributions from known point sources for markers correlated with wind direction. Black carbon (BC), volatile organic compounds (VOCs) and organic molecular markers were apportioned to sources using the Chemical Mass Balance (CMB) and Positive Matrix Factorization (PMF) receptor models. Diesel and gasoline mobile source factors were identified as the main sources of BC in the downtown Pittsburgh area, contributing 67% and 20% of the study-average BC. 13% of the BC was associated with a source factor tentatively identified as an industrial or regional source. The high time resolution of the TAG has the potential to provide important new insight into source apportionment efforts using organic molecular marker measurements.     

Impacts of future land use/land cover on wildfire occurrence in the Madrid region (Spain)

This paper assesses the relative importance of socioeconomic factors linked to fire occurrence through the simulation of future land use/land cover (LULC) change scenarios in the Madrid region (Spain). This region is a clear example of the socioeconomic changes that have been occurring over recent decades in the European Mediterranean as well as their impact on LULC and fire occurrence. Using the LULC changes observed between 1990 and 2006 as a reference, future scenarios were run up to 2025 with the conversion of land use and its effects model. Simultaneously, the relationship between LULC arrangement (interfaces) and historical fire occurrence was calculated using logistic regression analysis and used to quantify changes in future fire occurrence due to projected changes in LULC interfaces. The results revealed that it is possible to explain the probability of fire occurrence using only variables obtained from LULC maps, although the explanatory power of the model is low. In this context, border areas between some LULC types are of particular interest (i.e., urban/forest, grassland/forest and agricultural/forest interfaces). Results indicated that expected LULC changes in Euro-Mediterranean regions, particularly given the foreseeable increase in the wildland–urban interface, will substantially increase fire occurrence (up to 155 %). This underlines the importance of future LULC scenarios when planning fire prevention measures.     

Regional integration and local change: road paving, community connectivity, and social–ecological resilience in a tri-national frontier, southwestern Amazonia

Initiatives for global economic integration increasingly prioritize new infrastructure in relatively remote regions. Such regions have relatively intact ecosystems and provide valuable ecosystem services, which has stimulated debates over the wisdom of new infrastructure. Most prior research on infrastructure impacts highlights economic benefits, ecological damage, or social conflicts. We suggest a more integrative approach to regional integration by appropriating the concepts of connectivity from transport geography and social?Cecological resilience from systems ecology. Connectivity offers a means of observing the degree of integration between locations, and social?Cecological resilience provides a framework to simultaneously consider multiple consequences of regional integration. Together, they offer a spatial analysis of resilience that considers multiple dimensions of infrastructure impacts. Our study case is the southwestern Amazon, a highly biodiverse region which is experiencing integration via paving of the Inter-Oceanic Highway. Specifically, we focus on the ??MAP?? region, a tri-national frontier where Bolivia, Brazil, and Peru meet and which differs in the extent of highway paving. We draw on a tri-national survey of more than 100 resource-dependent rural communities across the MAP frontier and employ indicators for multiple dimensions of connectivity and social?Cecological resilience. We pursue a comparative analysis among regions and subregions with differing degrees of community connectivity to markets in order to evaluate their social?Cecological resilience. The findings indicate that connectivity and resilience have a multifaceted relationship, such that greater community connectivity corresponds to greater resilience in some respects but not others. We conclude by noting how our findings integrate those from heretofore largely disparate literatures on infrastructure. The integration of transport geography with resilience thought thus stands to advance the study of infrastructure impacts.     

Asthma and Air Pollution in Two Inner City Areas in New York City

The preliminary analysis of four months of emergency room visits for asthma in two inner city areas containing populations of similar socioeconomic, racial, and ethnic compositions, with similar day to day weather conditions but differing in their day to day levels of air pollution was made, and the relationship of visits to emergency rooms to daily temperature and air pollution levels measured in the areas, are described.

In Harlem no relationship between daily visits to emergency rooms and daily levels of either smokeshade or sulfur dioxide have been observed whereas in Brooklyn a relatively strong correlation between daily visits for asthma and daily levels of sulfur dioxide but not with smokeshade have been observed over and above the effect of temperature. In both areas there was a strong relationship between daily visits for asthma and the first cold spells of the fall season. The average male/female ratio for asthma visits to hospital emergency rooms of both areas in the age group under thirteen years of age was 1.7 and for the over thirteen years of age group was 0.6.

It appears from the data that Brooklyn presents a different picture for the environmental influence on asthma attacks. Even though it has been shown by previous investigators that asthmatics are sensitive to sulfur dioxide, we feel that in our case sulfur dioxide is not necessarily the causative agent, but might rather implicate some other confounding variable (most likely an environmental agent) that is disseminated in the general Bedford-Stuyvesant area in a similar day to day pattern to sulfur dioxide. We infer this from the fact that levels of sulfur dioxide were somewhat higher on the average in the Harlem area than they were in the Brooklyn area.     

Rationale for an Eight-Hour Ozone Standard

As part of the exposure assessment scheme for a community-based air pollution health effects study, 43 homes of study participants, located in two Houston neighborhoods, were monitored for weekly-average indoor formaldehyde levels by means of diffusion samplers. Consecutive 12-hour aldehyde sampling for one-week periods was conducted in 12 of the homes by means of pumps and impingers. In six houses where simultaneous monitoring with both methods occurred, good correlation between the results from the diffusion samplers and the standard impinger method was observed. Diffusion sampler precision was variable and lower than expected, and a small positive measurement bias could be inferred. The distribution of house-average indoor formaldehyde concentrations from diffusion monitoring was similar to that obtained during a previous housing survey in Houston, with concentrations in 19 percent of the homes exceeding 0.10 ppm. Formaldehyde levels in this group of conventional, mostly older homes could not be associated with smoking, cooking, home age or structure type. However, there was a statistically significant difference between mean indoor concentrations in the two neighborhoods.     

Can Basin Land Use Effects on Physical Characteristics of Streams Be Determined at Broad Geographic Scales?

The environmental setting (e.g., climate, topography, geology) and land use affect stream physical characteristics singly and cumulatively. At broad geographic scales, we determined the importance of environmental setting and land use in explaining variation in stream physical characteristics. We hypothesized that as the spatial scale decreased from national to regional, land use would explain more of the variation in stream physical characteristics because environmental settings become more homogeneous. At a national scale, stepwise linear regression indicated that environmental setting was more important in explaining variability in stream physical characteristics. Although statistically discernible, the amount of variation explained by land use was not remarkable due to low partial correlations. At level II ecoregion spatial scales (southeastern USA plains, central USA plains, and a combination of the western Cordillera and the western interior basins and ranges), environmental setting variables were again more important predictors of stream physical characteristics, however, as the spatial scale decreased from national to regional, the portion of variability in stream physical characteristics explained by basin land use increased. Development of stream habitat indicators of land use will depend upon an understanding of relations between stream physical characteristics and environmental factors at multiple spatial scales. Smaller spatial scales will be necessary to reduce the confounding effects of variable environmental settings before the effects of land use can be reliably assessed.     

The Weakness of Tight Ties: Why Scientists Almost Destroyed the Coachella Valley Multispecies Habitat Conservation Plan in Order to Save it

Two groups of biologists were responsible for an unprecedented delay in completing a endangered species habitat conservation plan in the Coachella Valley of southern California. While antagonism grew as each group relentlessly promoted their perspective on whether to add a few areas to the habitat preserve, their inability to resolve their differences was not simply a matter of mistrust or poor facilitation. I analyze how these biologists practiced science in a way that supported specific institutional and ecological relationships that in turn provided a setting in which each group’s biological expertise was meaningful, credible, and useful. This tight coupling between scientific practice and society meant that something was more important to these scientists than finishing the plan. For both factions of biologists, ensuring the survival of native species in the valley rested on their ability to catalyze institutional relationships that were compatible with their scientific practice. Understanding this co-production of science and the social order is a first step toward effectively incorporating different experts in negotiation and implementation of technically complex collaborative agreements.     

Species-specific tuning increases robustness to sampling bias in models of species distributions: An implementation with Maxent

Various methods exist to model a species’ niche and geographic distribution using environmental data for the study region and occurrence localities documenting the species’ presence (typically from museums and herbaria). In presence-only modelling, geographic sampling bias and small sample sizes represent challenges for many species. Overfitting to the bias and/or noise characteristic of such datasets can seriously compromise model generality and transferability, which are critical to many current applications - including studies of invasive species, the effects of climatic change, and niche evolution. Even when transferability is not necessary, applications to many areas, including conservation biology, macroecology, and zoonotic diseases, require models that are not overfit. We evaluated these issues using a maximum entropy approach (Maxent) for the shrew Cryptotis meridensis, which is endemic to the Cordillera de Mérida in Venezuela. To simulate strong sampling bias, we divided localities into two datasets: those from a portion of the species’ range that has seen high sampling effort (for model calibration) and those from other areas of the species’ range, where less sampling has occurred (for model evaluation). Before modelling, we assessed the climatic values of localities in the two datasets to determine whether any environmental bias accompanies the geographic bias. Then, to identify optimal levels of model complexity (and minimize overfitting), we made models and tuned model settings, comparing performance with that achieved using default settings. We randomly selected localities for model calibration (sets of 5, 10, 15, and 20 localities) and varied the level of model complexity considered (linear versus both linear and quadratic features) and two aspects of the strength of protection against overfitting (regularization). Environmental bias indeed corresponded to the geographic bias between datasets, with differences in median and observed range (minima and/or maxima) for some variables. Model performance varied greatly according to the level of regularization. Intermediate regularization consistently led to the best models, with decreased performance at low and generally at high regularization. Optimal levels of regularization differed between sample-size-dependent and sample-size-independent approaches, but both reached similar levels of maximal performance. In several cases, the optimal regularization value was different from (usually higher than) the default one. Models calibrated with both linear and quadratic features outperformed those made with just linear features. Results were remarkably consistent across the examined sample sizes. Models made with few and biased localities achieved high predictive ability when appropriate regularization was employed and optimal model complexity was identified. Species-specific tuning of model settings can have great benefits over the use of default settings.